Diagnostic tests that can be performed at the point of care of an individual, such as at the bedside of a patient, at a care provider location, or at the home of the patient, are becoming increasingly popular. Diagnostic tests include tests directed to identifying biomarkers such as Nucleic Acid, protein, and small molecules. Many of the diagnostic testing devices incorporate affinity based sensors which are considered to be the state-of-the-art in detection of biomarkers.
Affinity based biosensors function according to a “key-lock” principal in which a molecule with very high association factor to the biomarker of interest is used for detection. For example, a pregnancy test kit may incorporate a monoclonal antibody specific to a β-subunit of hCG (βhCG). The antibody is conjugated with a tag, e.g., gold, latex, or a fluorophore, which is used for detection. If the targeted molecule binds with the conjugated antibody, the tagged key-lock pair will be detectable such as by a visible test line.
ELISA plates and microarrays (e.g., Nucleic Acid, peptide, and protein) incorporate a similar principal. FIG. 1 depicts an ELISA assay 10 wherein antibodies 12 are immobilized on a substrate 14. The substrate 14 may be positioned within a well (not shown). A blocker 16 is provided to cover the surface of the substrate around the antibody 12. In a typical ELISA assay, a sample 18 is then added to the well in which the primary antibody 12 is immobilized. Next, the sample is incubated for some time. During incubation, the blocker 16 prevents the molecules of interest in the sample from binding to the surface of the substrate 14 in order to avoid false binding. During incubation, some of the molecules of interest 18 become bound with some of the antibodies 12 as depicted in FIG. 2. After incubation, the remaining sample is washed to remove the unbound molecules 18.
Subsequently, a secondary antibody 20 with a bound label 22 is added to the well, incubated, and washed resulting in the configuration of FIG. 3. As depicted in FIG. 3, the labeled secondary antibodies 20 are bound to the molecules of interest 18 that are in turn bound to the antibodies 12. Accordingly, the number of labels 22 bound by the antibodies 20 to the molecule of interest 18 is proportional to the concentration of the target molecule. Depending on the type of label used, the number of labels can be finally detected using colorimetry, amperometry, magnetometry, voltammetry, luminescence, or fluorescence detection. Other label-free antibody processes such as surface plasmon resonance may alternatively be used.
The quality of the diagnostic tests discussed above can be assessed using Limit of Detection (LoD) and Limit of Quantitation (LoQ) analysis. LoD, which is the minimum concentration of target molecules needed in order to create a large enough quantity of complexes that can be recognized by the available means of detection, is affected by the mutual affinity between a probe molecule and a target molecule, the density of probe molecules, incubation conditions, and the level of background and noise in the detection mechanism. As reported by Burtis, et al., “Tietz Textbook of Clinical Chemistry and Molecular Diagnostics,” Elsevier Saunders, 2005, the LoD for a particular assay is generally considered to be the concentration of target molecules that produces a signal 2-3 times greater than the average background signal.
The LoQ metric includes both an upper limit and a lower limit. The upper and lower limits as defined by Burtis, et al. “Tietz Textbook of Clinical Chemistry and Molecular Diagnostics,” Elsevier Saunders, 2005, are the highest and lowest concentrations, respectively, that can be quantitatively measured within an acceptable total error for the particular assay. Generally, the acceptable error for a particular assay in the United States is defined by the Food and Drug Administration based upon the standard deviation of so-called “gold standard tests”.
The range of concentrations between the lower LoQ and the upper LoQ for a particular assay is the dynamic range of the assay. The lower LoQ is related to the LoD which, as discussed above, is related to the affinity probe molecule density on the substrate. Thus, a high affinity probe molecule density is incorporated in many assays so as to increase the sensitivity of the particular assay. The upper LoQ, however, is typically a function of the maximum density or concentration of probe molecules that can be achieved in a particular assay.
Given a particular concentration of affinity probe molecules, the normalized signal obtained from a particular assay does not vary linearly with the concentration of the analyte of interest. By way of example, FIG. 4 depicts a response curve (RC). A “response curve” as that term is used herein is a curve showing the relationship between various concentrations of a molecule of interest in a plurality of samples and a plurality of quantitation signals obtained from the plurality of samples for a particular assay. In FIG. 4, a typical signal response versus target concentration for a particular assay is depicted as a response curve 30. Within the range of signals of FIG. 4, a lower LoQ is defined by the line 32 at about 10−12 mol/l while the upper LoQ is defined by the line 34 at about 10−10 mol/l. Between the lower LoQ 32 and the upper LoQ 34, the response curve 30 is shaped like an ogee. The dynamic range of the assay which produces the response curve 30 of FIG. 4 is about two orders of magnitude. The dynamic range of a typical assay is generally between 1 to 3 orders of magnitude.
The dynamic range of a particular assay limits the usefulness of the assay in applications wherein the expected variation in tested samples is several orders of magnitude. By way of example, detectable proteins in human serum range in abundance from grams to tenths of picograms per milliliter. Furthermore, serum protein abundance can change by as much as 10,000-fold on stimulation. As reported by S. F. Kingsmore, “Multiplexed protein measurement: technologies and applications of protein and antibody arrays,” Nature Reviews Drug Discovery, No. 4, pp. 310-320, 2006, many of the proteins that are most frequently measured, such as acute phase reactant pentraxins or chemokines, also exhibit large variations. Accordingly, the expression range for many biomolecules can span 6 orders of magnitude or more and a convenient assay should have an equal dynamic range while the dynamic range of a typical assay is generally between 1 to 3 orders of magnitude.
In multiplexed assays and microarrays the issue of narrowly limited dynamic range is especially relevant as detection of multiple biomarkers is critical for improving diagnostics. Microarrays, however, fall short of achieving the levels of quantification that established optimized tests, e.g., ELISA, can realize, even in conjunction with other time consuming lab techniques, e.g., serial dilution. Accordingly, while microarrays are heavily used and are experiencing an exponential growth, such usage is primarily directed to detection of molecules of interest rather than in quantification of molecules of interest. The use of multiplexed assays and microarrays even as detection mechanisms, however, is limited. For example, even healthy individuals carry markers which, when present in greater concentrations, can indicate the presence of a disease.
In response to limited upper LoQs in earlier assays, some manufacturers have developed substrates which allow for higher densities of the immobilized probe molecule and thus higher dynamic range. Such substrates generally include a three dimensional structure which, while providing a greater dynamic range, may also increase the assay variation. Some of such approaches result in the binding kinetics and stability of probe molecules and may even cause reduction in dynamic range.
Another approach to increasing the dynamic range of assays is to perform a series of dilutions on a sample such that one of the diluted samples provides a target concentration that is within the dynamic detection range of an assay. Such an approach has been reported by Patrick Domnanich, et al. “Protein microarray for the analysis of human melanoma biomarkers,” Sensors and Actuators B: Chemical, Vol. “In Press, Corrected Proof”, 2008. This simple yet effective approach has the disadvantage of requiring a considerable number of additional steps (including multiple dilutions and multiple runs of the actual assay) which add to the test time and increases costs and operating expenses.
Recently, other solutions have been proposed to increase the dynamic range of an assay. One such solution for a point of care device disclosed in U.S. Patent Application Publication No. 2006/0019404 A1 includes the use of two strips with different dynamic ranges. Different dynamic ranges can be achieved by using different antibodies and, by combining the results, a wider dynamic range for the assay can be achieved. Other solutions reported by N. Ohmura, et al., “Combinational Use of Antibody Affinities in an Immunoassay for Extension of Dynamic Range and Detection of Multiple Analytes,” Analytical Chemistry, Vol. 75, No. 1, pp. 104-110, 2003, and A. P. Drabovich, et al., “Smart Aptamers Facilitate Multi-Probe Affinity Analysis of Proteins with Ultra-Wide Dynamic Range of Measured Concentrations,” Journal of the American Chemical Society, Vol. 129, No. 23, pp. 7260-7260, 2007, include the use of two or more probe molecules, either antibodies or aptamers, with different affinities for the analyte in order to extend the dynamic range. Such approaches require an overlap between the dynamic ranges of the different probe molecules used and are thus limited by the availability of multiple antibodies or aptamers having the desired affinities.
A need exists for a device and method of performing a quantization assay incorporating low cost antibodies. A further need exists for low cost assays including multiplexed assays, protein arrays, lateral flow devices, sandwich assays, competitive assays, or bead based arrays which provide accurate quantization results and a method of using such arrays. Methods and devices which provide relatively linear results would be a further benefit.